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https://www.selleckchem.com/products/ly3009120.html The linear array's one-dimensional spatial geometry is simple but suffices for univariate direction finding, i.e., is adequate for the estimation of an incident source's direction-of-arrival relative to the linear array axis. However, this nominal one-dimensional ideality could be often physically compromised in the real world, as the constituent sensors may dislocate three-dimensionally from their nominal positions. For example, a towed array is subject to ocean-surface waves and to oceanic currents [Tichavsky and Wong (2004). IEEE Trans. Sign. Process. 52(1), 36-47]. This paper analyzes how a nominally linear array's one-dimensional direction-finding accuracy would be degraded by the three-dimensional random dislocation of the constituent sensors. This analysis derives the hybrid Cramér-Rao bound (HCRB) of the arrival-angle estimate in a closed form expressed in terms of the sensors' dislocation statistics. Surprisingly, the sensors' dislocation could improve and not necessarily degrade the HCRB, depending on the dislocation variances but also on the incident source's arrival angle and the signal-to-noise power ratio.This paper investigates the performance of active noise control (ANC) systems with two reflecting surfaces that are placed vertically on ground in parallel. It employs the modal expansion method and the boundary element method to calculate the noise reduction of the systems with infinitely large and finite size reflecting surfaces, respectively. Both experimental and simulation results show that the noise reduction of the system can be significantly increased after optimizing the surface separation distance and their locations with the sound sources. It is found that the sound radiation of the primary source can be completely reduced in principle if the surface interval is less than half the wavelength and the source line is perpendicular to the surfaces for infinitely large reflecting surfaces. Even

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